Tracking Patterns in Self-Regulated Learning Using Students' Self-Reports and Online Trace Data
For decades, self-report instruments - which rely heavily on students' perceptions and beliefs - have been the dominant way of measuring motivation and strategy use. An event-based measure based on online trace data arguably has the potential to remove analytical restrictions of self-report mea...
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| Main Authors: | , , , , |
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| Format: | Book |
| Published: |
EARLI,
2020-03-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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| Summary: | For decades, self-report instruments - which rely heavily on students' perceptions and beliefs - have been the dominant way of measuring motivation and strategy use. An event-based measure based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to triangulate constructs suggested in theory and measured using self-reported data with revealed online traces of learning behaviour. The results show that online trace data of learning behaviour are complementary to self-reports, as they explained a unique proportion of variance in student academic performance and reveal that self-reports explain more variance in online learning behaviour of prior weeks than variance in learning behaviour in succeeding weeks. Student motivation is, however, to a lesser extent captured with online trace data, likely because of its covert nature. In that respect, it is of importance to recognize the crucial role of self-reports in capturing student learning holistically. This manuscript is 'frontline' in the sense that event-based measurement methodologies using online trace data are relatively unexplored. The comparison with self-report data made in this manuscript sheds new light on the added value of innovative and traditional methods of measuring motivation and strategy use. |
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| Item Description: | 10.14786/flr.v8i3.497 2295-3159 |